Michael Iliadis

I am a senior machine learning engineer at Captricity. My focus is in machine learning for computer vision and particularly in image document recognition and handwriting recognition.

Before that, I was a research scientist at SONY US Research Center where I worked on semantic segmentation for SONY products.

I received my Ph.D. degree in EECS from Northwestern University in 2016 where I worked under the supervision of Aggelos K. Katsaggelos in the Image and Video Laboratory (IVPL). I received my M.S. degree in Computer Science from the University of Bath, UK in 2009 and the B.S. degree in Digital Systems from the University of Piraeus, Greece in 2008.

Email  /  CV  /  Thesis  /  Google Scholar  /  LinkedIn

Research

My research focuses in machine learning/deep learning for computer vision and image processing applications. Recent projects include image document/text analysis and recognition, semantic segmentation for scene understanding, video compressive sensing and face recognition.

DeepBinaryMask: Learning a Binary Mask for Video Compressive Sensing
Michael Iliadis, Leonidas Spinoulas, Aggelos K. Katsaggelos
Arxiv, 2017
bibtex

We propose a novel encoder-decoder neural network model called DeepBinaryMask for video compressive sensing. The proposed framework is an end-to-end model where the sensing matrix is trained along with the video reconstruction.

Deep Fully-Connected Networks for Video Compressive Sensing
Michael Iliadis, Leonidas Spinoulas, Aggelos K. Katsaggelos
Elsevier Digital Signal Processing, 2017
bibtex

A deep learning framework for video compressive sensing.

Robust and Low-Rank Representation for Fast Face Identification with Occlusions
Michael Iliadis, Haohong Wang, Rafael Molina, Aggelos K. Katsaggelos
IEEE Transactions on Image Processing (TIP), 2017
bibtex / code

A fast iterative method to address the face identification problem with block occlusions.

Multi-Model Robust Error Correction for Face Recognition
Michael Iliadis, Leonidas Spinoulas, Albert S. Berahas, Haohong Wang, Aggelos K. Katsaggelos
International Conference Image Processing (ICIP), 2016
bibtex

The proposed formulation allows the simultaneous use of various loss functions for modeling the residual in face images.

Block Based Video Alignment with Linear time and Space Complexity
Armin Kappeler, Michael Iliadis, Haohong Wang, Aggelos K. Katsaggelos
International Conference Image Processing (ICIP), 2016
bibtex

We propose a fast, robust and memory efficient video sequence alignment algorithm which has linear space and time complexity.

Sparse Representation and Least Squares-based Classification in Face Recognition
Michael Iliadis, Leonidas Spinoulas, Albert S. Berahas, Haohong Wang, Aggelos K. Katsaggelos
European Signal Processing Conference (EUSIPCO), 2014
bibtex / code

Effectively, our method combines the sparsity-based approaches with additional least-squares steps.

Virtual touring - A Content Based Image Retrieval application
Michael Iliadis, Seunghwan Yoo, Xin Xin, Aggelos K. Katsaggelos
International Conference on Multimedia and Expo Workshops (ICMEW), 2013
bibtex

A content based image retrieval application for searching landmarks and buildings in a city using a smartphone.

Video Compressive Sensing using Multiple Measurement Vectors
Michael Iliadis, Jeremy Watt, Leonidas Spinoulas, Aggelos K. Katsaggelos
International Conference Image Processing (ICIP), 2013
bibtex / Top 10% Paper Recognition

The approach takes advantage of Multiple Measurement Vectors (MMV), seeking for significantly sparser solutions, assuming that the solution vectors have similar sparsity structure.

Teaching

EECS 214: Data Structures and Data Management - Spring 2015, 2016

GEN_ENG 205: Engineering Analysis - Winter 2015


I copied the source code of this website from here.